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Hello and welcome to this learn-by-doing course: Deploying and Managing the EFK Stack on Kubernetes. I’m Vijin Palazhi, and together with Harshita Joshi we’ll guide you through hands-on labs that teach how to deploy, scale, monitor, and secure the EFK stack. This course is aimed at DevOps engineers, system administrators, and cloud professionals who want practical experience deploying and operating Elasticsearch, Fluentd, and Kibana on Kubernetes for reliable log aggregation, analysis, and visualization. You’ll learn how the EFK stack improves application observability and operational intelligence in production-like Kubernetes environments.
A blue gradient presentation slide titled "Deploying and Managing the EFK Stack on Kubernetes" with the subtitle "Learn By Doing." The slide includes a small "© Copyright KodeKloud" notice in the bottom-left.
What you’ll work with: By the end of this course, you will be able to:
  • Deploy and configure Elasticsearch clusters on Kubernetes
  • Integrate Fluentd for cluster-wide log collection and buffering
  • Set up Kibana dashboards for log analysis and alerting
  • Monitor, scale, and secure the EFK stack for production workloads
A white card displaying the Elasticsearch, Fluentd, and Kibana logos with their names underneath and a small Kubernetes icon in the top-left. The image also shows a “© Copyright KodeKloud” notice in the bottom-left.
How the hands-on labs are organized
  • Overview tab: conceptual background, architecture diagrams, configuration options, and links to additional resources.
  • Tasks tab: step-by-step, actionable tasks where you apply commands and configuration to the live cluster.
  • Terminal: the integrated terminal is your workspace to run kubectl, edit manifests, and interact with the cluster.
  • Hint and Solution tabs: use these if you need guidance; Check validates your completed tasks.
Use the Overview tab for theory and the Tasks tab for hands-on steps. The terminal inside the lab is where you run commands against the provided cluster.
Example of the terminal header you may see in the lab interface:
Quick reference: lab UI components Course roadmap (what you’ll cover)
  • Fundamentals: Kubernetes concepts relevant to logging and stateful applications
  • Elasticsearch: deploying StatefulSets, persistence, index management, and scaling
  • Fluentd: DaemonSet-based log collection, buffering, and parsing pipelines
  • Kibana: connecting to Elasticsearch, building dashboards, and role-based access
  • Advanced topics: configuration management, monitoring metrics, autoscaling, backups, and securing communication and data
Each module builds on the previous one to create a clear learning path — from Kubernetes basics to advanced EFK configuration and operational best practices.
A simple diagram showing two semicircles on a horizontal baseline: an orange left semicircle labeled "Basics of Kubernetes" with a Kubernetes helm icon, and a purple right semicircle labeled "Complex configurations and Management techniques" with a cloud-and-gear icon, connected by a dotted arc. The image includes a small "© Copyright KodeKloud" notice in the corner.
Getting started
  • Open the first lab and follow the Overview to understand the objectives.
  • Use the Tasks tab to apply the configurations and run commands in the integrated terminal.
  • Validate your work using the Check button; revisit hints or the solution if you get stuck.
Do not run destructive or unrelated commands against the lab cluster. Stay within the task scope to avoid affecting shared lab resources.
Further reading and references What are you waiting for? Begin the first lab and start deploying the EFK stack.

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